Monthly Archives: September 2011

The True Cost of Government Guarantees

The August bankruptcy at the solar panel manufacturer Solyndra has generated a predictable political kerfluffle, since the company had received $527 million in loan guarantees from the Obama Administration. The political issues raised by the case are fair game. But I’m more interested in a more general issue:

What is the true cost to taxpayers of loan guarantees?

Obviously, we learn the cost of a particular loan guarantee, like the one for the bankrupt Solyndra, ex post—it’s the amount of money the government has to payout to the creditors. But what is the right estimated cost ex ante?

Coincidentally, August was also the month that saw the CBO publish a report on the true cost to taxpayers of Federal Loan Guarantees for the Construction of Nuclear Power Plants.

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The Volcker Rule & Trader Compensation

A Bloomberg article details how a draft of the Volcker Rule uses the structure of trader compensation to distinguish between proprietary trading and market making. Exactly right!

Lesson from UBS on trader compensation

The case of the $2.3 billion trading loss at UBS holds many lessons for any company that trades derivatives. Remember, UBS wants to claim its trader was a rogue that victimized the company. There was a time that a bank could shout ‘rogue’ as an effective excuse of senior management. But that time is now long past. There have been plenty of penetrating questions asked about the self-evident shoddiness of UBS’ control systems. Another area that deserves scrutiny is the compensation system. How is a trader’s pay determined?

Pay should be for performance. But what counts as performance?

The metrics for performance on a proprietary trading portfolio should be different from the metrics for performance by a market maker. A market maker ought to be compensated, in part, for how successfully s/he is hedging trades. For a market maker, outsized gains on the unhedged component should not count towards a bonus, whereas for a trader running a proprietary portfolio, they should.

How was performance measured at UBS’ Delta One desk? If the traders were being rewarded based on the total profitability of the desk, then UBS was incentivizing them to speculate, and the Delta One desk shouldn’t be described as customer facing or market making.

This same lesson applies to non-financial companies that hedge through their own trading desk. The metrics for performance on hedging should incentivize minimizing risk. The metrics should measure risk reduction. When the desk reports big profits — after netting out the matched positions — that’s a bad sign, not a good one.

If you pay out bonuses when bets payoff, be prepared to see some bets that lose big, too. It’s not a rogue trader if the risky bets are rewarded by the compensation system.


It is becoming clear that the UBS scandal that rocked financial markets last week is not just about a single trader suddenly gone awry. UBS’s controls – both in risk management and auditing – failed miserably. Top bankers in the investment banking arm of UBS didn’t have a clue about what was going on in the trading desks and in the back office. When a kid can so easily blow a $2.3 billion hole in the balance sheet, and cause so much damage to the reputation of a top tier bank, there’s something awfully wrong.

But the failures of the system go beyond UBS alone. Kweku Adoboli made trades that apparently didn’t require prompt confirmation with its counterparties. Why? Because in Europe, where UBS’s Delta-One trading desk is based, the vast majority of trading in exchange-traded funds (ETF) occurs over the counter (OTC), in bilateral trades. The rapid growth in ETF trading (a profit center) has outpaced spending in back-office and reporting activities (a cost). According to the Wall Street Journal, a report published in 2009 states that over three quarters of European ETF trading didn’t require any reporting.  The Bank of England, among other supervisory authorities, has called attention to the growing complexity and interconnectedness of ETFs. Unregulated OTC trading also makes them obscure. The inherent lack of transparency of OTC markets provides a fertile ground for misrepresentation and outright fraud. It is also likely that opacity makes it much harder to measure the risks taken by ambitious traders.

The European Commission is now carefully saying that it will look into the possible regulatory implications of the case. The Commission, scared to death by the banks’ threat to leave if new regulations are imposed, has ignored the lessons of the 2008 Jerome Kerviel affair, responsible for Societé General’s $7.2 billion mishap with ETFs and related OTC derivatives transactions. It would serve the European Union well if it learned from the US, where ETF trades are reported and cleared through public and open exchanges. No opacity, less room for cheating.

The Cosmetics of Collateral Transformation

Responding to the new regulatory reforms such as the Dodd-Frank Act in the US, banks are now marketing “collateral transformation” services. A good source for various materials on this issue is Tracey Alloway’s coverage in FT Alphaville.

What are these services? How are they connected to the reforms? Should we be worried?

Collateral transformation is a fancy name for a particular type of loan, as shown in the top three boxes of the figure below. A company/fund trading a standardized derivatives contract cleared by a central counterparty (CCP) must post a margin. Initial margins are posted with cash and government securities; variation margins are posted with cash. Holding cash for the purpose of posting margins exacts an opportunity cost, for it earns less than if invested in less liquid securities. The bank steps in and offers to lend the company/fund the cash for collateral at the CCP, and the company/fund provides less liquid securities it holds in the balance sheet to the bank as collateral. In addition to providing the company/fund with liquidity, the bank structures the arrangement to easily mesh with the mechanics of trading, settlement and so on, so as to minimize the administrative costs to the institutions that are its customers. See this brochure and this article.

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Risk and return in the eye of the beholder

The corporate finance practice team at McKinsey & Co has joined the long line of people looking at the large cash hoard being assembled by corporations and asking “why?”. In an article in the McKinsey Quarterly, they suggest a surprising answer:

One factor that might go unnoticed, however, is the surprisingly strong role of decision biases in the investment decision-making process—a role that revealed itself in a recent McKinsey Global Survey. Most executives, the survey found, believe that their companies are too stingy, especially for investments expensed immediately through the income statement and not capitalized over the longer term. Indeed, about two-thirds of the respondents said that their companies underinvest in product development, and more than half that they underinvest in sales and marketing and in financing start-ups for new products or new markets. Bypassed opportunities aren’t just a missed opportunity for individual companies: the investment dearth hurts whole economies and job creation efforts as well.

The article provides a useful examination of biases in decision making. Many managers would concur that a million dollars lost on a bad investment in the recent past would tighten the finances of a company much more than a million dollars won would relax the constraint. This may be especially so in a period when creditors are deleveraging and equity holders are quite wary about bad news.

The McKinsey piece reminds us that a project is not just the Power Point slides and the numbers in a spreadsheet, but what these are in the eye of the beholder.  But how does that relate to the global picture of corporate cash hoards? It’s one thing to be humble about the quality of decision making and the biases that affect it. It’s an entirely other thing to connect those biases to the very large aggregate economic fluctuations in the global economy, including the cash that companies seem to think it is prudent to husband very carefully right now. When did prudence became a bias?

Central Clearing can economize on collateral

Reforming the financial system involves not only the grand public battles over legislation and rulemaking, but also the substantial trenchwork that falls to staffers in the many agencies responsible for carrying out the mandates. And it is heartening to observe this work advance. One of the many interesting analyses being produced en route is a study by Daniel Heller and Nicholas Vause at the Bank for International Settlements (BIS), the international organization of central banks. The purpose of the report is to produce an estimate of the financial resources that Central Counterparties (CCPs) would need to safely clear interest rate and credit default swaps. Central clearing of derivative trades is one of the major mandates of the Dodd-Frank Financial Reform Act in the U.S. and of comparable reforms in Europe.

In a number of our previous posts, we have emphasized that end-users have much to gain from the central clearing mandate—see here, here, here and here. Central clearing creates the possibility to reduce the total amount of credit risk in the system, lowering the overall costs to the various parties using derivatives, including non-financial companies seeking to hedge their commercial risk. One reflection of how risks can be minimized, depending upon how the mandates are implemented, shows up in Graph 6 of this BIS study, reproduced below.

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Cash & Carry, #4: Other resolutions to the puzzle

We began this series of posts recapping the finding that a currency carry trade investment has historically produced high return relative to the low risk. This finding is not consistent with models in finance that focus on the correlation between an investment’s return and the return on some benchmark stock portfolio. Using these models, and looking at the historical distribution of returns, the carry trade looks like a good bet, even accounting for bad outcomes. Posts #2 and #3 in the series reported on one route of the research effort to explain the puzzle, which attributes the abnormal return to the “peso problem”. But other researchers have been pursuing different routes. To wrap up this series, we’ll quickly mention some of this work.

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